15 citations · 35 across the 9 of their papers we have counts for
9 papers
A Consistent and Scalable Algorithm for Best Subset Selection in Single Index Models
Borui Tang, Jin Zhu, Junxian Zhu +2
Analysis of high-dimensional data has led to increased interest in both single index models (SIMs) and the best-subset selection. SIMs provide an interpretable and flexible modelin…
Best-Subset Selection in Generalized Linear Models: A Fast and Consistent Algorithm via Splicing Technique
Junxian Zhu, Jin Zhu, Borui Tang +3
In high-dimensional generalized linear models, it is crucial to identify a sparse model that adequately accounts for response variation. Although the best subset section has been w…
High Dimensional Portfolio Selection with Cardinality Constraints
Jin-Hong Du, Yifeng Guo, Xueqin Wang
The expanding number of assets offers more opportunities for investors but poses new challenges for modern portfolio management (PM). As a central plank of PM, portfolio selection…
Quantiles, Ranks and Signs in Metric Spaces
Hang Liu, Xueqin Wang, Jin Zhu +1
Non-Euclidean data become more prevalent in practice, necessitating the development of a framework for statistical inference analogous to that for Euclidean data. Quantile is one o…
abess: A Fast Best Subset Selection Library in Python and R
Jin Zhu, Xueqin Wang, Liyuan Hu +5
We introduce a new library named abess that implements a unified framework of best-subset selection for solving diverse machine learning problems, e.g., linear regression, classifi…
A Splicing Approach to Best Subset of Groups Selection
Yanhang Zhang, Junxian Zhu, Jin Zhu +1
Best subset of groups selection (BSGS) is the process of selecting a small part of non-overlapping groups to achieve the best interpretability on the response variable. It has attr…
Computational analysis of pathological image enables interpretable prediction for microsatellite instability
Jin Zhu, Wangwei Wu, Yuting Zhang +4
Microsatellite instability (MSI) is associated with several tumor types and its status has become increasingly vital in guiding patient treatment decisions. However, in clinical pr…
Best Subset Selection in Reduced Rank Regression
Canhong Wen, Weiyu Li, Junxian Zhu +1
We design a new algorithm on the best subset selection model in reduced rank regression.
BeSS: An R Package for Best Subset Selection in Linear, Logistic and CoxPH Models
Canhong Wen, Aijun Zhang, Shijie Quan +1
We introduce a new R package, BeSS, for solving the best subset selection problem in linear, logistic and Cox's proportional hazard (CoxPH) models. It utilizes a highly efficient a…